Triple
T71546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California–Nevada border |
E1431
|
entity |
| Predicate | hasSectionType |
P2563
|
FINISHED |
| Object | mountain boundary |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: mountain boundary | Statement: [California–Nevada border, hasSectionType, mountain boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionType Context triple: [California–Nevada border, hasSectionType, mountain boundary]
-
A.
hasSegmentType
chosen
Indicates that an entity is associated with, or classified by, a particular type or category of segment within a larger structure or sequence.
-
B.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
C.
hasStructureType
Indicates that an entity possesses or is classified by a specific structural type or configuration.
-
D.
hasNodeType
Indicates that an entity is associated with, or classified as, a specific type of node within a structured system or model.
-
E.
hasRecordType
Indicates that an entity is associated with or classified under a specific type or category of record.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.